Video surveillance involves archiving data from the security cameras, 24 hours a day and 365 days of the year. With current support for 1080p HD and newer 4K megapixel video formats, the data obtained from cameras place a lot of load on the underlying storage system. The storage must be flexible enough to accommodate different configurations of data and exhibit high performance of read/write operations. It is an added bonus if the solution is cost effective and easily scalable to accommodate an increase in the number of surveillance cameras in the future.
The biggest vendors in the distributed storage market offer storage solutions that are associated with special hardware units, each available with a GUI for managing the units. These solutions are both inflexible and expensive as adding additional compute or storage to your initial setup would require purchasing a new hardware unit and installing it into your existing solution. Also, achieving a level of data redundancy implies having additional hardware units that can be used to setup RAID configurations.
Having a software defined storage means that the storage and data management functions would be handed over to an intelligent software and you can simply use your existing hardware for the storage setup. This greatly drives own costs as you will not need to purchase special hardware for your distributed solution or need specialized configurations.
The reliability of fault recovery and the data redundancy is also achieved at a lower price as, RAID is substituted with a software adaptation called erasure coding that does not need additional hardware for achieving redundancy and inconsistencies in data would be dealt in the same software.
A feature of this software defined storage is hyper-converged architecture, in which you integrate compute, storage and networking resources. It reduces IT costs, improves efficiency and creates a more agile environment for your storage solution.
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In case of a storage solution for a video surveillance project, a hyper-converged solution means that load from the cameras would be distributed evenly to all the storage nodes, resulting in increased speed along with the elimination of single point entry bottlenecks. Also, the support for an integrated cache results in extremely high IOPS with low latency. Horizontal synchronization of nodes ensures high availability of the storage solution and the ability to recreate data missing from broken nodes in the clusters’ empty space, resulting in only momentary decrease in capacity until the node has been replaced.
The hyper-converged solution decouples workloads from the physical infrastructure to enable greater mobility, and offer VM-centric policies and management. This eliminates the need for infrastructure specialists and provides greater flexibility.